The value of multiple
dataset calibration versus model complexity for improving the
performance of hydrological models in mountain catchments

The assessment of snow, glacier and rainfall runoff contribution to discharge in mountain streams is of major importance for an adequate water resource management. Such contributions can be
estimated via hydrological models, provided that the modeling adequately accounts for snow and glacier melt, as well as rainfall runoff. We present a multi-dataset calibration approach to
estimate runoff composition using hydrological models with three levels of complexity. For this purpose the code of the conceptual runoff model HBV-light was enhanced to allow calibration and
validation of simulations against glacier mass balances, satellite-derived snow cover area and measured discharge. Three levels of complexity of the model were applied to glacierized catchments
in Switzerland, ranging from 39km2 to 103km2. The results indicate that all three observational datasets are reproduced adequately by the model, allowing an accurate
estimation of the runoff composition in the three mountain streams. However, calibration against only runoff leads to unrealistic snow and glacier melt rates. Based on these results we recommend
using all three observational datasets in order to constrain model parameters and compute snow, glacier and rain contributions. Finally, based on the comparison of model performance of different
complexities we postulate that the availability and use of different datasets to calibrate hydrological models might be more important than model complexity to achieve realistic estimations of
runoff composition.